Search

Although coronary computed tomographic angiography (CCTA) has been a robust diagnostic tool to identify anatomical significance of coronary artery disease (CAD), the utility of CCTA to assess hemodynamic significance of CAD remains unclear. We investigated the diagnostic performance of transluminal attenuation gradient (TAG) and fractional flow reserve derived from CCTA (FFRCT) to predict lesion-specific ischemia by invasive FFR. We identified 103 patients with suspected or known CAD enrolled from the DISCOVER-FLOW and DeFACTO studies who underwent invasive coronary angiography with FFR and high quality ≥64-slice CCTA. Diagnostic performance for predicting abnormal invasive FFR (≤0.80) was assessed for TAG [≤−1.1 HU/mm by the area under the curve (AUC) by receiver-operating characteristic curve analysis (ROC)], FFRCT (≤0.80), and CCTA stenosis (≥50 %). On a per-vessel analysis (n = 146), 52 vessels (35.6 %) had ischemia by invasive FFR. The sensitivity, specificity, positive predictive value and negative predictive value were 53.8, 45.7, 35.4, 64.2 % for TAG, 82.7, 74.5, 64.2, 88.6 % for FFRCT, 84.6, 39.4, 43.6, 82.2 % for CCTA stenosis, respectively. The AUC by ROC curve analysis for FFRCT (0.79) demonstrated greater discrimination of hemodynamic ischemia compared to TAG (0.50, p

Background: Pericoronary adipose tissue (PCAT) attenuation has been associated with coronary inflammation and can be evaluated with coronary computed tomography angiography. The aims of this study were to compare the PCAT attenuation across precursors of culprit and nonculprit lesions of patients with acute coronary syndrome versus stable coronary artery disease (CAD)., Methods: In this case-control study, patients with suspected CAD who underwent coronary computed tomography angiography were included. Patients who developed an acute coronary syndrome within 2 years after the coronary computed tomography angiography scan were identified, and patients with stable CAD (defined as any coronary plaque ≥30% luminal diameter stenosis) were 1:2 propensity score matched for age, sex, and cardiac risk factors. The mean PCAT attenuation was analyzed at lesion level and compared between precursors of culprit lesions, nonculprit lesions, and stable coronary plaques., Results: In total, 198 patients (age 62±10 years, 65% male) were selected, including 66 patients who developed an acute coronary syndrome and 132 propensity matched patients with stable CAD. Overall, 765 coronary lesions were analyzed (culprit lesion precursors: n=66; nonculprit lesion precursors: n=207; and stable lesions: n=492). Culprit lesion precursors had larger total plaque volume, fibro-fatty plaque volume, and low-attenuation plaque volume compared to nonculprit and stable lesions. The mean PCAT attenuation was significantly higher across culprit lesion precursors compared to nonculprit and stable lesions (-63.8±9.7 Hounsfield units versus -68.8±10.6 Hounsfield units versus -69.6±10.6 Hounsfield units, respectively; P <0.001), whereas the mean PCAT attenuation around nonculprit and stable lesions was not significantly different ( P =0.99)., Conclusions: The mean PCAT attenuation is significantly increased across culprit lesion precursors in patients with acute coronary syndrome, compared to nonculprit lesions of these patients and to lesions of patients with stable CAD, which may suggest a higher intensity of inflammation. PCAT attenuation on coronary computed tomography angiography may be a novel marker to identify high-risk plaques.

Pericoronary adipose tissue (PCAT) attenuation, derived from coronary computed tomography angiography (CCTA), is associated with coronary artery inflammation. Values for PCAT attenuation in men and women without atherosclerosis on CCTA are lacking. The aim of the current study was to assess the mean PCAT attenuation in individuals without coronary artery atherosclerosis on CCTA. Data on PCAT attenuation in men and women without coronary artery atherosclerosis on CCTA were included in this retrospective analysis. The PCAT attenuation was analyzed from the proximal part of the right coronary artery (RCA), the left anterior descending artery (LAD), and the left circumflex artery (LCx). For patient level analyses the mean PCAT attenuation was defined as the mean of the three coronary arteries. In 109 individuals (mean age 45 ± 13 years; 44% men), 320 coronary arteries were analyzed. The mean PCAT attenuation of the overall population was - 64.4 ± 8.0 HU. The mean PCAT attenuation was significantly lower in the LAD compared with the LCx and RCA (- 67.8 ± 7.8 HU vs - 62.6 ± 6.8 HU vs - 63.6 ± 7.9 HU, respectively, p < 0.001). In addition, the mean PCAT attenuation was significantly higher in men vs. women in all three coronary arteries (LAD: - 65.7 ± 7.6 HU vs - 69.4 ± 7.6 HU, p = 0.014; LCx: - 60.6 ± 7.4 HU vs - 64.3 ± 5.9 HU, p = 0.008; RCA: -61.7 ± 7.9 HU vs - 65.0 ± 7.7 HU, p = 0.029, respectively). The current study provides mean PCAT attenuation values, derived from individuals without CAD. Moreover, the mean PCAT attenuation is lower in women vs. men. Furthermore, the mean PCAT attenuation is significantly lower in the LAD vs LCx and RCA., (© 2022. The Author(s).)

Background: The association between the change in vessel inflammation, as quantified by perivascular adipose tissue (PVAT) density, and the progression of coronary atherosclerosis remains to be determined., Objectives: The purpose of this study was to explore the association between the change in PVAT density and the progression of total and compositional plaque volume (PV)., Methods: Patients were selected from a prospective multinational registry. Patients who underwent serial coronary computed tomography angiography studies with ≥2-year intervals and were scanned with the same tube voltage at baseline and follow-up were included. Total and compositional PV and PVAT density at baseline and follow-up were quantitatively analyzed for every lesion. Multivariate linear regression models using cluster analyses were constructed., Results: A total of 1,476 lesions were identified from 474 enrolled patients (mean age 61.2 ± 9.3 years; 65.0% men). The mean PVAT density was -74.1 ± 11.5 HU, and total PV was 48.1 ± 83.5 mm 3 (19.2 ± 44.8 mm 3 of calcified PV and 28.9 ± 51.0 mm 3 of noncalcified PV). On multivariate analysis (adjusted for clinical risk factors, medication use, change in lipid levels, total PV at baseline, luminal HU attenuation, location of lesions, and tube voltage), the increase in PVAT density was positively associated with the progression of total PV (estimate = 0.275 [95% CI: 0.004-0.545]; P = 0.047), driven by the association with fibrous PV (estimate = 0.245 [95% CI: 0.070-0.420]; P = 0.006). Calcified PV progression was not associated with the increase in PVAT density (P > 0.050)., Conclusions: Increase in vessel inflammation represented by PVAT density is independently associated with the progression of the lipid component of coronary atherosclerotic plaques. (Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging [PARADIGM]; NCT02803411)., Competing Interests: Funding Support and Author Disclosures This work was supported by the Korea Medical Device Development Fund grant funded by the Korea government (the Ministry of Science and ICT; the Ministry of Trade, Industry and Energy; the Ministry of Health and Welfare, Republic of Korea, the Ministry of Food and Drug Safety) (Project Number: 202016B02). The study was also funded in part by a grant from the Dalio Foundation. Dr Leipsic has served as a consultant for and holds stock options in HeartFlow and Circle CVI. Drs Kitslaar and Reiber are employees of Medis Medical Imaging. Dr Samady has served on the scientific advisory board of Philips; has equity interest in Covanos Inc; and has received a research grant from Medtronic. Dr Lin has received grant support from GE Healthcare. Dr Min has received funding from GE Healthcare; has served on the scientific advisory board of Arineta and GE Healthcare; and has an equity interest in and is an employee of Cleerly, Inc. Dr Chang has received funding from the Leading Foreign Research Institute Recruitment Program through the National Research Foundation (NRF) of Korea funded by the Ministry of Science and ICT (MSIT) (Grant No. 2012027176). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2022 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Purpose: To provide comparative prognostic information of coronary atherosclerotic plaque volume and stenosis assessment in patients with suspected coronary artery disease (CAD)., Methods: We followed 372 patients with suspected or known CAD enrolled in the CORE320 study for 2 years after baseline 320-detector row cardiac CT scanning and invasive quantitative coronary angiography (QCA). CT images were analyzed for coronary calcium scanning (CACS), semi-automatically derived total percent atheroma volume (PAV), segment stenosis score (SSS), in addition to traditional stenosis assessment (≥ 50%) by CT and QCA for (1) 30-day revascularization and (2) major adverse cardiac events (MACE). Area under the receiver operating characteristic curve (AUC) was used to compare accuracy of risk prediction., Results: Sixty percent of patients had obstructive CAD by QCA with 23% undergoing 30-day revascularization and 9% experiencing MACE at 2 years. Most late events (20/32) were revascularization procedures. Prediction of 30-day revascularization was modest (AUC range 0.67-0.78) but improved after excluding patients with known CAD (AUC range 0.73-0.86, p < 0.05 for all). Similarly, prediction of MACE improved after excluding patients with known CAD (AUC range 0.58-0.73 vs. 0.63-0.77). CT metrics of atherosclerosis burden performed overall similarly but stenosis assessment was superior for predicting 30-day revascularization., Conclusions: Angiographic and coronary atherosclerotic plaque metrics perform only modestly well for predicting 30-day revascularization and 2-year MACE in high risk patients but improve after excluding patients with known CAD. Atherosclerotic plaque metrics did not yield incremental value over stenosis assessment for predicting events that predominantly consisted of revascularization procedures., Clinical Trial Registration: NCT00934037.

Purpose: Currently, coronary plaque changes are manually compared between a baseline and follow-up coronary computed tomography angiography (CCTA) images for long-term coronary plaque development investigation. We propose an automatic method to measure the plaque thickness change over time., Methods: We model the lumen and vessel wall for both the baseline coronary artery tree (CAT-BL) and follow-up coronary artery tree (CAT-FU) as smooth three-dimensional (3D) surfaces using a subdivision fitting scheme with the same coarse meshes by which the correspondence among these surface points is generated. Specifically, a rigid point set registration is used to transform the coarse mesh from the CAT-FU to CAT-BL. The plaque thickness and the thickness difference is calculated as the distance between corresponding surface points. To evaluate the registration accuracy, the average distance between manually defined markers on clinical scans is calculated. Artificial CAT-BL and CAT-FU pairs were created to simulate the plaque decrease and increase over time., Results: For 116 pairs of markers from nine clinical scans, the average marker distance after registration was 0.95 ± 0.98 mm (two times the voxel size). On the 10 artificial pairs of datasets, the proposed method successfully located the plaque changes. The average of the calculated plaque thickness difference is the same as the corresponding created value (standard deviation ± 0.1 mm)., Conclusions: The proposed method automatically calculates local coronary plaque thickness differences over time and can be used for 3D visualization of plaque differences. The analysis and reporting of coronary plaque progression and regression will benefit from an automatic plaque thickness comparison., (© 2019 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)

Objectives: This study sought to investigate the performance of various cardiac computed tomography (CT)-derived atherosclerotic plaque metrics for predicting provocable myocardial ischemia., Background: The association of coronary arterial diameter stenosis with myocardial ischemia is only modest, but cardiac CT provides several other, readily available atherosclerosis metrics, which may have incremental value., Methods: The study analyzed 873 nonstented coronary arteries and their myocardial perfusion territories in 356 patients (mean 62 years of age) enrolled in the CORE320 (Coronary Artery Evaluation using 320-row Multidetector Computed Tomography Angiography and Myocardial Perfusion) study. Myocardial perfusion defects in static CT perfusion imaging were graded at rest and after adenosine in 13 myocardial segments using a 4-point scale. The summed difference score was calculated by subtracting the summed rest score from the summed stress score. Reversible ischemia was defined as summed difference score ≥1. In a sensitivity analysis, results were also provided using single-photon emission computed tomography (SPECT) as the reference standard. Vessel based predictor variables included maximum percent diameter stenosis, lesion length, coronary calcium score, maximum cross-sectional calcium arc, percent atheroma volume (PAV), low-attenuation atheroma volume, positive (external) vascular remodeling, and subjective impression of "vulnerable plaque." The study used logistic regression models to assess the association of plaque metrics with myocardial ischemia., Results: In univariate analysis, all plaque metrics were associated with reversible ischemia. In the adjusted logistic model, only maximum percent diameter stenosis (1.26; 95% confidence interval: 1.15 to 1.38) remained an independent predictor. With SPECT as outcome variable, PAV and "vulnerable" plaque remained predictive after adjustment. In vessels with intermediate stenosis (40% to 70%), no single metric had clinically meaningful incremental value., Conclusions: Various plaque metrics obtained by cardiac CT predict provocable myocardial ischemia by CT perfusion imaging through their association with maximum percent stenosis, while none had significant incremental value. With SPECT as reference standard, PAV and "vulnerable plaque" remained predictors of ischemia after adjustment but the predictive value added to stenosis assessment alone was small., (Copyright © 2019 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

A dedicated software package that could semi-automatically assess differences in aortic maximal cross-sectional diameters from consecutive CT scans would most likely reduce the post-processing time and effort by the physicians. The aim of this study was to present and assess the quality of a new tool for the semi-automatic quantification of thoracic aorta dilation dimensions. Twenty-nine patients with two CTA scans of the thoracic aorta for which the official clinical report indicated an increase in aortic diameters were included in the study. Aortic maximal cross-sectional diameters of baseline and follow-up studies generated semi-automatically by the software were compared with corresponding manual measurements. The semi-automatic measurements were performed at seven landmarks defined on the baseline scan by two operators. Bias, Bland-Altman plots and intraclass correlation coefficients were calculated between the two methods and, for the semi-automatic software, also between two observers. The average time difference between the two scans of a single patient was 1188 ± 622 days. For the semi-automatic software, in 2 out of 29 patients, manual interaction was necessary; in the remaining 27 patients (93.1%), semi-automatic results were generated, demonstrating excellent intraclass correlation coefficients (all values ≥ 0.91) and small differences, especially for the proximal aortic arch (baseline: 0.19 ± 1.30 mm; follow-up: 0.44 ± 2.21 mm), the mid descending aorta (0.37 ± 1.64 mm; 0.37 ± 2.06 mm), and the diaphragm (0.30 ± 1.14 mm; 0.37 ± 1.80 mm). The inter-observer variability was low with all errors in diameters ≤ 1 mm, and intraclass correlation coefficients all ≥ 0.95. The semi-automatic tool decreased the processing time by 40% (13 vs. 22 min). In this work, a semi-automatic software package that allows the assessment of thoracic aorta diameters from baseline and follow-up CTs (and their differences), was presented, and demonstrated high accuracy and low inter-observer variability.

Purpose: Improve mapping and registration of longitudinal view on histopathology vessels in a three-dimensional alignment procedure for postmortem quantitative coronary plaque analyses. This new procedure is applied and results shown using calcified coronary plaque analyses within post-mortem computed tomography angiography (PMCTA), optical coherence tomography (OCT) and the gold standard of histopathology., Results: In total, 338 annotated histopathology images were included, 166 PMCTA transversal images and 285 OCT images were aligned in the comparison. The results from the comparison using the alignment procedure showed overall that the calcified plaques seem to be overestimated by PMCTA and underestimated by OCT., Conclusions: The 3D fusion approach, aligning the images of PMCTA, OCT and histopathology as gold standard allowed for a slice-based comparison of the different modalities. The results showed that PMCTA overestimates the calcified plaques while OCT underestimates these, compared to histopathology., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Purpose: Automatically extracted coronary artery trees (CATs) from coronary computed tomography angiography images could contain incorrect extractions which require manual corrections before they can be used in clinical practice. A model-guided method for improving the extracted CAT is described to automatically detect potential incorrect extractions and improve them., Methods: The proposed method is a coarse-to-fine approach. A coarse improvement is first applied on all vessels in the extracted CAT, and then a fine improvement is applied only on vessels with higher clinical significance. Based upon a decision tree, the proposed method automatically and iteratively performs improvement operations for the entire extracted CAT until it meets the stop criteria. The improvement in the extraction quality obtained by the proposed method is measured using a scoring system. 18 datasets were used to determine optimal values for the parameters involved in the model-guided method and 122 datasets were used for evaluation., Results: Compared to the initial automatic extractions, the proposed method improves the CATs for 122 datasets from an average quality score of 87 ± 6 to 93 ± 4. The developed method is able to run within 2 min on a typical workstation. The difference in extraction quality after automatic improvement is negatively correlated with the initial extraction quality (R = - 0.694, P < 0.001)., Conclusion: Without deteriorating the initially extracted CATs, the presented method automatically detects incorrect extractions and improves the CATs to an average quality score of 93 guided by anatomical statistical models.

Background: To investigate the impact of diabetes on coronary artery total plaque volume (TPV) and adverse events in long-term follow-up., Methods: One-hundred-and-eight diabetic patients were matched to 324 non-diabetic patients, with respect to age, sex, body-mass index, hypertension, smoking habits, LDL and HDL cholesterol, family history for CAD as well as aspirin and statin medication. In all patients, TPV was quantified from coronary CT angiographies (CTA) using dedicated software. All-cause mortality, acute coronary syndrome and late revascularisation (>90 days) served as combined endpoint., Results: Patients were followed for 5.6 years. The endpoint occurred in 18 (16.7%) diabetic and 26 (8.0%) non-diabetic patients (odds ratio 2.3, p = 0.03). Diabetic patients had significantly higher TPV than non-diabetic patients (55.1 mm³ [IQR: 6.2 and 220.4 mm³] vs. 24.9 mm³ [IQR: 0 and 166.7 mm³], p = 0.02). A TPV threshold of 110.5 mm³ provided good separation of diabetic and non-diabetic patients at higher and lower risk for adverse events. Noteworthy, diabetic and non-diabetic patients with a TPV<110.5 mm³ had comparable outcome (hazard ratio: 1.3, p = 0.59), while diabetic patients with TPV>110.5 mm³ had significantly higher incidence of adverse events (hazard ratio 2.3, p = 0.03) compared to non-diabetic patients with TPV>110.5 mm³. There was incremental prognostic value in diabetic and non-diabetic patients over the Framingham Risk Score (Integrated Discrimination Improvement: 0.052 and 0.012, p for both <0.05)., Conclusion: Diabetes is associated with significantly higher TPV, which is independent of other CAD risk factors. Quantification of TPV improves the identification of diabetic patients at higher risk for future adverse events., (Copyright © 2019 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.)

Background High-risk plaque (HRP) features as detected by coronary computed tomography angiography (CTA) predict acute coronary syndrome (ACS). We sought to determine whether coronary CTA-specific definitions of HRP improve discrimination of patients with ACS as compared with definitions from intravascular ultrasound (IVUS). Methods and Results In patients with suspected ACS, randomized to coronary CTA in the ROMICAT II (Rule Out Myocardial Infarction/Ischemia Using Computer Assisted Tomography II) trial, we retrospectively performed semiautomated quantitative analysis of HRP (including remodeling index, plaque burden as derived by plaque area, low computed tomography attenuation plaque volume) and degree of luminal stenosis and analyzed the performance of traditional IVUS thresholds to detect ACS. Furthermore, we derived CTA-specific thresholds in patients with ACS to detect culprit lesions and applied those to all patients to calculate the discriminatory ability to detect ACS in comparison to IVUS thresholds. Of 472 patients, 255 patients (56±7.8 years; 63% men) had coronary plaque. In 32 patients (6.8%) with ACS, culprit plaques (n=35) differed from nonculprit plaques (n=172) with significantly greater values for all HRP features except minimal luminal area (significantly lower; all P<0.01). IVUS definitions showed good performance while minimal luminal area (odds ratio: 6.82; P=0.014) and plaque burden (odds ratio: 5.71; P=0.008) were independently associated with ACS but not remodeling index (odds ratio: 0.78; P=0.673). Optimized CTA-specific thresholds for plaque burden (area under the curve: 0.832 versus 0.676) and degree of stenosis (area under the curve: 0.826 versus 0.721) showed significantly higher diagnostic performance for ACS as compared with IVUS-based thresholds (all P<0.05) with borderline significance for minimal luminal area (area under the curve: 0.817 versus 0.742; P=0.066). Conclusions CTA-specific definitions of HRP features may improve the discrimination of patients with ACS as compared with IVUS-based definitions. CLINICAL TRIAL REGISTRATION URL: https://www.clinicaltrials.gov . Unique identifier: NCT01084239.

Serial measurements of coronary plaque volume have been used to evaluate drug efficacy in atherosclerotic progression. However, the usefulness of computed tomography for this purpose is unknown. We investigated whether the change in total plaque volume on coronary computed tomographic angiography is associated with the change in segment plaque volume on intravascular ultrasound. We prospectively enrolled 11 consecutive patients (mean age, 56.3 ± 5 yr; 6 men) who were to undergo serial invasive coronary angiographic examinations with use of grayscale intravascular ultrasound and coronary computed tomography, performed <180 days apart at baseline and from 1 to 2 years later. Subjects underwent 186 serial measurements of total plaque volume on coronary computed tomography and 22 of segmental plaque volume on intravascular ultrasound. We used semiautomated software to examine percentage relationships and changes between total plaque and segmental plaque volumes. No significant correlations were found between percentages of total coronary and segment coronary plaque volume, nor between normalized coronary plaque volume. However, in the per-patient analysis, there were strong correlations between the imaging methods for changes in total coronary and segment coronary plaque volume ( r =0.62; P =0.04), as well as normalized plaque volume ( r =0.82; P =0.002). Per-patient change in plaque volume on coronary computed tomography is significantly associated with that on intravascular ultrasound. Computed tomographic angiography may be safer and more widely available than intravascular ultrasound for evaluating atherosclerotic progression in coronary arteries. Larger studies are warranted.

Background: To investigate the incremental prognostic value of low-attenuation plaque volume (LAPV) from coronary CT angiography datasets., Methods: Quantification of LAPV was performed using dedicated software equipped with an adaptive plaque tissue algorithm in 1577 patients with suspected CAD. A combination of death and acute coronary syndrome was defined as primary endpoint. To assess the incremental prognostic value of LAPV, parameters were added to a baseline model including clinical risk and obstructive coronary artery disease (CAD), a baseline model including clinical risk and calcium scoring (CACS) and a baseline model including clinical risk and segment involvement score (SIS)., Results: Patients were followed for 5.5 years either by telephone contact, mail or clinical visits. The primary endpoint occurred in 30 patients. Quantified LAPV provided incremental prognostic information beyond clinical risk and obstructive CAD (c-index 0.701 vs. 0.767, p < .001), clinical risk and CACS (c-index 0.722 vs. 0.771, p < .01) and clinical risk and SIS (c-index 0.735 vs. 0.771, p < .01. A combined approach using quantified LAPV and clinical risk significantly improved the stratification of patients into different risk categories compared to clinical risk alone (categorical net reclassification index 0.69 with 95% CI 0.27 and 0.96, p < .001). The combined approach classified 846 (53.6%) patients as low risk (annual event rate 0.04%), 439 (27.8%) patients as intermediate risk (annual event rate 0.5%) and 292 (18.5%) patients as high risk (annual event rate 0.99%)., Conclusion: Quantification of LAPV provides incremental prognostic information beyond established CT risk patterns and permits improved stratification of patients into different risk categories., (Copyright © 2018 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.)

Semi-automated software can provide quantitative assessment of atherosclerotic plaques on coronary CT angiography (CTA). The relationship between established qualitative high-risk plaque features and quantitative plaque measurements has not been studied. We analyzed the association between quantitative plaque measurements and qualitative high-risk plaque features on coronary CTA. We included 260 patients with plaque who underwent coronary CTA in the Rule Out Myocardial Infarction/Ischemia Using Computer Assisted Tomography (ROMICAT) II trial. Quantitative plaque assessment and qualitative plaque characterization were performed on a per coronary segment basis. Quantitative coronary plaque measurements included plaque volume, plaque burden, remodeling index, and diameter stenosis. In qualitative analysis, high-risk plaque was present if positive remodeling, low CT attenuation plaque, napkin-ring sign or spotty calcium were detected. Univariable and multivariable logistic regression analyses were performed to assess the association between quantitative and qualitative high-risk plaque assessment. Among 888 segments with coronary plaque, high-risk plaque was present in 391 (44.0%) segments by qualitative analysis. In quantitative analysis, segments with high-risk plaque had higher total plaque volume, low CT attenuation plaque volume, plaque burden and remodeling index. Quantitatively assessed low CT attenuation plaque volume (odds ratio 1.12 per 1 mm 3 , 95% CI 1.04-1.21), positive remodeling (odds ratio 1.25 per 0.1, 95% CI 1.10-1.41) and plaque burden (odds ratio 1.53 per 0.1, 95% CI 1.08-2.16) were associated with high-risk plaque. Quantitative coronary plaque characteristics (low CT attenuation plaque volume, positive remodeling and plaque burden) measured by semi-automated software correlated with qualitative assessment of high-risk plaque features.

An automatic coronary artery tree labeling algorithm is described to identify the anatomical segments of the extracted centerlines from coronary computed tomography angiography (CCTA) images. This method will facilitate the automatic lesion reporting and risk stratification of cardiovascular disease. Three-dimensional (3D) models for both right dominant (RD) and left dominant (LD) coronary circulations were built. All labels in the model were matched with their possible candidates in the extracted tree to find the optimal labeling result. In total, 83 CCTA datasets with 1149 segments were included in the testing of the algorithm. The results of the automatic labeling were compared with those by two experts. In all cases, the proximal parts of main branches including LM were labeled correctly. The automatic labeling algorithm was able to identify and assign labels to 89.2% RD and 83.6% LD coronary tree segments in comparison with the agreements of the two experts (97.6% RD, 87.6% LD). The average precision of start and end points of segments was 92.0% for RD and 90.7% for LD in comparison with the manual identification by two experts while average differences in experts is 1.0% in RD and 2.2% in LD cases. All cases got similar clinical risk scores as the two experts. The presented fully automatic labeling algorithm can identify and assign labels to the extracted coronary centerlines for both RD and LD circulations.

Aims: The aim of this study was to examine the effect of the daughter branches on the haemodynamics and the potential prediction of atherosclerotic plaque development as well as the best flow division model for accurate blood flow modelling., Methods and Results: We analysed computed tomography coronary angiography retrospective data portraying 17 coronary artery bifurcations in 15 patients recruited into the PROSPECT MSCT study. Baseline and three-year follow-up imaging data were used to reconstruct coronary artery anatomy. In the baseline models blood flow simulations were performed using three flow division approaches: stress-free, Murray's law and Doriot's fit. Blood flow simulation was also performed omitting the daughter branch. The association between ESS estimated in models that incorporated the daughter branches and lumen reduction was higher than the cases where the side branch was omitted. Murray's law provides the most accurate results when comparing the different flow division models. More specifically, low ESS is a predictor of significant lumen reduction (p=0.007), plaque burden increase (p=0.0006) and necrotic core change (p=0.025)., Conclusions: The ESS distribution in coronary models including the daughter branches and based on the calculations implementing Murray's law allows more accurate prediction of atherosclerotic evolution than ESS estimated in models including only the main vessel.

Purpose: The quantification of vessel wall morphology and plaque burden requires vessel segmentation, which is generally performed by manual delineations. The purpose of our work is to develop and evaluate a new 3D model-based approach for carotid artery wall segmentation from dual-sequence MRI., Methods: The proposed method segments the lumen and outer wall surfaces including the bifurcation region by fitting a subdivision surface constructed hierarchical-tree model to the image data. In particular, a hybrid segmentation which combines deformable model fitting with boundary classification was applied to extract the lumen surface. The 3D model ensures the correct shape and topology of the carotid artery, while the boundary classification uses combined image information of 3D TOF-MRA and 3D BB-MRI to promote accurate delineation of the lumen boundaries. The proposed algorithm was validated on 25 subjects (48 arteries) including both healthy volunteers and atherosclerotic patients with 30% to 70% carotid stenosis., Results: For both lumen and outer wall border detection, our result shows good agreement between manually and automatically determined contours, with contour-to-contour distance less than 1 pixel as well as Dice overlap greater than 0.87 at all different carotid artery sections., Conclusions: The presented 3D segmentation technique has demonstrated the capability of providing vessel wall delineation for 3D carotid MRI data with high accuracy and limited user interaction. This brings benefits to large-scale patient studies for assessing the effect of pharmacological treatment of atherosclerosis by reducing image analysis time and bias between human observers., (© 2017 American Association of Physicists in Medicine.)

Background: Automatic accurate measuring of the aortic annulus and determination of the optimal angulation of X-ray projection are important for the trans-catheter aortic valve replacement (TAVR) procedure. The objective of this study was to present a novel fully automatic methodology for the quantification of the aortic annulus in computed tomography angiography (CTA) images., Methods: CTA datasets of 26 patients were analyzed retrospectively with the proposed methodology, which consists of a knowledge-based segmentation of the aortic root and detection of the orientation and size of the aortic annulus. The accuracy of the methodology was determined by comparing the automatically derived results with the reference standard obtained by semi-automatic delineation of the aortic root and manual definition of the annulus plane., Results: The difference between the automatic annulus diameter and the reference standard by observer 1 was 0.2±1.0mm, with an inter-observer variability of 1.2±0.6mm. The Pearson correlation coefficient for the diameter was good (0.92 for observer 1). For the first time, a fully automatic tool to assess the optimal projection curves was presented and validated. The mean difference between the optimal projection curves calculated based on the automatically defined annulus plane and the reference standard was 6.4° in the cranial/caudal (CRA/CAU) direction. The mean computation time was short with around 60s per dataset., Conclusion: The new fully automatic and fast methodology described in this manuscript not only provided precise measurements about the aortic annulus size with results comparable to experienced observers, but also predicted optimal X-ray projection curves from CTA images., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Purpose: Investigate the influence of adaptive statistical iterative reconstruction (ASIR) and the model-based IR (Veo) reconstruction algorithm in coronary computed tomography angiography (CCTA) images on quantitative measurements in coronary arteries for plaque volumes and intensities., Methods: Three patients had three independent dose reduced CCTA performed and reconstructed with 30% ASIR (CTDI vol at 6.7 mGy), 60% ASIR (CTDI vol 4.3 mGy) and Veo (CTDI vol at 1.9 mGy). Coronary plaque analysis was performed for each measured CCTA volumes, plaque burden and intensities., Results: Plaque volume and plaque burden show a decreasing tendency from ASIR to Veo as median volume for ASIR is 314 mm 3 and 337 mm 3 -252 mm 3 for Veo and plaque burden is 42% and 44% for ASIR to 39% for Veo. The lumen and vessel volume decrease slightly from 30% ASIR to 60% ASIR with 498 mm 3 -391 mm 3 for lumen volume and vessel volume from 939 mm 3 to 830 mm 3 . The intensities did not change overall between the different reconstructions for either lumen or plaque., Conclusion: We found a tendency of decreasing plaque volumes and plaque burden but no change in intensities with the use of low dose Veo CCTA (1.9 mGy) compared to dose reduced ASIR CCTA (6.7 mGy & 4.3 mGy), although more studies are warranted., (Copyright © 2016 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.)

Aim: To investigate the efficacy of low-density lipoprotein (LDL) transport simulation in reconstructed arteries derived from computed tomography coronary angiography (CTCA) to predict coronary segments that are prone to progress., Methods and Results: Thirty-two patients admitted with an acute coronary event who underwent 64-slice CTCA after percutaneous coronary intervention and at 3-year follow-up were included in the analysis. The CTCA data were used to reconstruct the coronary anatomy of the untreated vessels at baseline and follow-up, and LDL transport simulation was performed in the baseline models. The computed endothelial shear stress (ESS), LDL concentration, and CTCA-derived plaque characteristics were used to identify predictors of substantial disease progression (defined as an increase in the plaque burden at follow-up higher than two standard deviations of the intra-observer variability of the expert who performed the analysis). Fifty-eight vessels were analysed. High LDL concentration [odds ratio (OR): 2.16; 95% confidence interval (CI): 1.64-2.84; P = 0.0054], plaque burden (OR: 1.40; 95% CI: 1.13-1.72; P = 0.0017), and plaque area (OR: 3.46; 95% CI: 2.20-5.44; P≤ 0.0001) were independent predictors of a substantial disease progression at follow-up. The ESS appears as a predictor of disease progression in univariate analysis but was not an independent predictor when the LDL concentration was entered into the multivariate model. The accuracy of the model that included the LDL concentration was higher than the accuracy of the model that included the ESS (65.1 vs. 62.5%)., Conclusions: LDL transport modelling appears a better predictor of atherosclerotic disease progression than the ESS, and combined with the atheroma characteristics provided by CTCA is able to detect with a moderate accuracy segments that will exhibit a significant plaque burden increase at mid-term follow-up., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2016. For permissions please email: journals.permissions@oup.com.)

Background and Aims: We aimed at investigating whether diabetes is associated with progression in coronary plaque components., Methods: We identified 142 study subjects undergoing serial coronary computed tomography angiography. The resulting propensity score was applied 1:1 to match diabetic patients to non-diabetic patients for clinical risk factors, prior coronary stenting, coronary artery calcium (CAC) score and the serial scan interval, resulting in the 71 diabetes and 71 non-diabetes patients. Coronary plaque (total, calcified, non-calcified including fibrous, fibrous-fatty and low attenuation plaque [LAP]) volume normalized by total coronary artery length was measured using semi-automated plaque software and its change overtime between diabetic and non-diabetic patients was evaluated., Results: The matching was successful without significant differences between the two groups in all matched variables. The baseline volumes in each plaque also did not differ. During a mean scan interval of 3.4 ± 1.8 years, diabetic patients showed a 2-fold greater progression in normalized total plaque volume (TPV) than non-diabetes patients (52.8 mm 3 vs. 118.3 mm 3 , p = 0.005). Multivariable linear regression model revealed that diabetes was associated with normalized TPV progression (β 72.3, 95%CI 24.3-120.3). A similar trend was observed for the non-calcified components, but not calcified plaque (β 3.8, 95%CI -27.0-34.7). Higher baseline CAC score was found to be associated with total, non-calcified and calcified plaque progression. However, baseline non-calcified volume but not CAC score was associated with LAP progression., Conclusions: The current study among matched patients indicates diabetes is associated with a greater plaque progression. Our results show the need for strict adherence of diabetic patients to the current preventive guidelines., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Purpose: The purpose of this study was to study the effect of iterative reconstruction (IR) software on quantitative plaque measurements in coronary computed tomography angiography (CCTA)., Methods: Thirty patients with a three clinical risk factors for coronary artery disease (CAD) had one CCTA performed. Images were reconstructed using FBP, 30% and 60% adaptive statistical IR (ASIR). Coronary plaque analysis was performed as per patient and per vessel (LM, LAD, CX and RCA) measurements. Lumen and vessel volumes and plaque burden measurements were based on automatic detected contours in each reconstruction. Lumen and plaque intensity measurements and HU based plaque characterization were based on corrected contours copied to each reconstruction., Results: No significant changes between FBP and 30% ASIR were found except for lumen- (-2.53 HU) and plaque intensities (-1.28 HU). Between FBP and 60% ASIR the change in total volume showed an increase of 0.94%, 4.36% and 2.01% for lumen, plaque and vessel, respectively. The change in total plaque burden between FBP and 60% ASIR was 0.76%. Lumen and plaque intensities decreased between FBP and 60% ASIR with -9.90 HU and -1.97 HU, respectively. The total plaque component volume changes were all small with a maximum change of -1.13% of necrotic core between FBP and 60% ASIR., Conclusions: Quantitative plaque measurements only showed modest differences between FBP and the 60% ASIR level. Differences were increased lumen-, vessel- and plaque volumes, decreased lumen- and plaque intensities and a small percentage change in the individual plaque component volumes., (Copyright © 2016 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.)

Extraction of the aorto-femoral vessel trajectory is important to utilize computed tomography angiography (CTA) in an integrated workflow of the image-guided work-up prior to trans-catheter aortic valve replacement (TAVR). The aim of this study was to develop a new, fully-automated technique for the extraction of the entire arterial access route from the femoral artery to the aortic root. An automatic vessel tracking algorithm was first used to find the centerline that connected the femoral accessing points and the aortic root. Subsequently, a deformable 3D-model fitting method was used to delineate the lumen boundary of the vascular trajectory in the whole-body CTA dataset. A validation was carried out by comparing the automatically obtained results with semi-automatically obtained results from two experienced observers. The whole framework was validated on whole body CTA datasets of 36 patients. The average Dice similarity indexes between the segmentations of the automatic method and observer 1 for the left ilio-femoral artery, the right ilio-femoral artery and the aorta were 0.977 ± 0.030, 0.980 ± 0.019, 0.982 ± 0.016; the average Dice similarity indexes between the segmentations of the automatic method and observer 2 were 0.950 ± 0.040, 0.954 ± 0.031 and 0.965 ± 0.019, respectively. The inter-observer variability resulted in a Dice similarity index of 0.954 ± 0.038, 0.952 ± 0.031 and 0.969 ± 0.018 for the left ilio-femoral artery, the right ilio-femoral artery and the aorta. The average minimal luminal diameters (MLDs) of the ilio-femoral artery were 6.03 ± 1.48, 5.70 ± 1.43 and 5.52 ± 1.32 mm for the automatic method, observer 1 and observer 2 respectively. The MLDs of the aorta were 13.43 ± 2.54, 12.40 ± 2.93 and 12.08 ± 2.40 mm for the automatic method, observer 1 and observer 2 respectively. The automatic measurement overestimated the MLD slightly in the ilio-femoral artery at the average by 0.323 mm (SD = 0.49 mm, p < 0.001) compared to observer 1 and by 0.51 mm (SD = 0.71 mm, p < 0.001) compared to observer 2. The proposed segmentation approach can automatically provide reliable measurements of the entire arterial accessing route that can be used to support TAVR procedures. To the best of our knowledges, this approach is the first fully automatic segmentation method of the whole aorto-femoral vessel trajectory in CTA images.

We enhance intravascular ultrasound virtual histology (VH) tissue characterization by fully automatic quantification of the acoustic shadow behind calcified plaque. VH is unable to characterize atherosclerosis located behind calcifications. In this study, the quantified acoustic shadows are considered calcified to approximate the real dense calcium (DC) plaque volume. In total, 57 patients with 108 coronary lesions were included. A novel post-processing step is applied on the VH images to quantify the acoustic shadow and enhance the VH results. The VH and enhanced VH results are compared to quantitative computed tomography angiography (QTA) plaque characterization as reference standard. The correlation of the plaque types between enhanced VH and QTA differs significantly from the correlation with unenhanced VH. For DC, the correlation improved from 0.733 to 0.818. Instead of an underestimation of DC in VH with a bias of 8.5 mm(3), there was a smaller overestimation of 1.1 mm(3) in the enhanced VH. Although tissue characterization within the acoustic shadow in VH is difficult, the novel algorithm improved the DC tissue characterization. This algorithm contributes to accurate assessment of calcium on VH and could be applied in clinical studies.

Background: Total atherosclerotic plaque burden assessment by CT angiography (CTA) is a promising tool for diagnosis and prognosis of coronary artery disease (CAD) but its validation is restricted to small clinical studies. We tested the feasibility of semi-automatically derived coronary atheroma burden assessment for identifying patients with hemodynamically significant CAD in a large cohort of patients with heterogenous characteristics., Methods: This study focused on the CTA component of the CORE320 study population. A semi-automated contour detection algorithm quantified total coronary atheroma volume defined as the difference between vessel and lumen volume. Percent atheroma volume (PAV = [total atheroma volume/total vessel volume] × 100) was the primary metric for assessment (n = 374). The area under the receiver operating characteristic curve (AUC) determined the diagnostic accuracy for identifying patients with hemodynamically significant CAD defined as ≥50% stenosis by quantitative coronary angiography and associated myocardial perfusion abnormality by SPECT., Results: Of 374 patients, 139 (37%) had hemodynamically significant CAD. The AUC for PAV was 0.78 (95% confidence interval [CI] 0.73-0.83) compared with 0.84 [0.79-0.88] by standard expert CTA interpretation (p = 0.02). Accuracy for both CTA (0.91 [0.87, 0.96]) and PAV (0.86 [0.81-0.91]) increased after excluding patients with history of CAD (p < 0.01 for both). Bland-Altman analysis revealed good agreement between two observers (bias of 280.2 mm(3) [161.8, 398.7])., Conclusions: A semi-automatically derived index of total coronary atheroma volume yields good accuracy for identifying patients with hemodynamically significant CAD, though marginally inferior to CTA expert reading. These results convey promise for rapid, reliable evaluation of clinically relevant CAD., (Copyright © 2016 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.)

Background: Although several previous studies have demonstrated that aged garlic extract (AGE) inhibits the progression of coronary artery calcification, its effect on noncalcified plaque (NCP) has been unclear., Objective: This study investigated whether AGE reduces coronary plaque volume measured by cardiac computed tomography angiography (CCTA) in patients with metabolic syndrome (MetS)., Methods: Fifty-five patients with MetS (mean ± SD age: 58.7 ± 6.7 y; 71% men) were prospectively assigned to consume 2400 mg AGE/d (27 patients) or placebo (28 patients) orally. Both groups underwent CCTA at baseline and follow-up 354 ± 41 d apart. Coronary plaque volume, including total plaque volume (TPV), dense calcium (DC), NCP, and low-attenuation plaque (LAP), were measured based upon predefined intensity cutoff values. Multivariable linear regression analysis, adjusted for age, gender, number of risk factors, hyperlipidemia medications, history of coronary artery disease, scan interval time, and baseline %TPV, was performed to examine whether AGE affected each plaque change., Results: The %LAP change was significantly reduced in the AGE group compared with the placebo group (-1.5% ± 2.3% compared with 0.2% ± 2.0%, P = 0.0049). In contrast, no difference was observed in %TPV change (0.3% ± 3.3% compared with 1.6% ± 3.0%, P = 0.13), %NCP change (0.2% ± 3.3% compared with 1.4% ± 2.9%, P = 0.14), and %DC change (0.2% ± 1.4%, compared with 0.2% ± 1.7%, P = 0.99). Multivariable linear regression analysis found a beneficial effect of AGE on %LAP regression (β: -1.61; 95% CI: -2.79, -0.43; P = 0.008)., Conclusions: This study indicates that the %LAP change was significantly greater in the AGE group than in the placebo group. Further studies are needed to evaluate whether AGE has the ability to stabilize vulnerable plaque and decrease adverse cardiovascular events. This trial was registered at clinicaltrials.gov as NCT01534910., (© 2016 American Society for Nutrition.)

Objective: To evaluate the diagnostic performance of automated coronary atherosclerotic plaque quantification (QCT) by different users (expert/non-expert/automatic)., Methods: One hundred fifty coronary artery segments from 142 patients who underwent coronary computed tomography angiography (CCTA) and intravascular ultrasound (IVUS) were analyzed. Minimal lumen area (MLA), maximal lumen area stenosis percentage (%AS), mean plaque burden percentage (%PB), and plaque volume were measured semi-automatically by expert, non-expert, and fully automatic QCT analyses, and then compared to IVUS., Results: Between IVUS and expert QCT analysis, the correlation coefficients (r) for the MLA, %AS, %PB, and plaque volume were excellent: 0.89 (p < 0.001), 0.84 (p < 0.001), 0.91 (p < 0.001), and 0.94 (p < 0.001), respectively. There were no significant differences in the mean parameters (all p values >0.05) except %AS (p = 0.01). The automatic QCT analysis showed comparable performance to non-expert QCT analysis, showing correlation coefficients (r) of the MLA (0.80 vs. 0.82), %AS (0.82 vs. 0.80), %PB (0.84 vs. 0.73), and plaque volume (0.84 vs. 0.79) when they were compared to IVUS, respectively., Conclusion: Fully automatic QCT analysis showed clinical utility compared with IVUS, as well as a compelling performance when compared with semiautomatic analyses., Key Points: • Coronary CTA enables the assessment of coronary atherosclerotic plaque. • High-risk plaque characteristics and overall plaque burden can predict future cardiac events. • Coronary atherosclerotic plaque quantification is currently unfeasible in practice. • Quantitative computed tomography coronary plaque analysis software (QCT) enables feasible plaque quantification. • Fully automatic QCT analysis shows excellent performance.

Potentially, Agatston coronary artery calcium (CAC) score could be calculated on contrast computed tomography coronary angiography (CTA). This will make a separate non-contrast CT scan superfluous. This study aims to assess the performance of a novel fully automatic algorithm to detect and quantify the Agatston CAC score in contrast CTA images. From a clinical registry, 20 patients were randomly selected for each CAC category (i.e. 0, 1-99, 100-399, 400-999, ≥1,000). The Agatston CAC score on non-contrast CT was calculated manually, while the novel algorithm was used to automatically detect and quantify Agatston CAC score in contrast CTA images. The resulting Agatston CAC scores were validated against the non-contrast images. A total of 100 patients (60 ± 11 years, 63 men) were included. The median CAC score on non-contrast CT was 145 (IQR 5-760), whereas the contrast CTA CAC score was 170 (IQR 23-594) (P = 0.004). The automatically computed CAC score showed a high correlation (R = 0.949; P < 0.001) and intra-class correlation (R = 0.863; P < 0.001) with non-contrast CT CAC score. Moreover, agreement within CAC categories was good (κ 0.588). Fully automatic detection of Agatston CAC score on contrast CTA is feasible and showed high correlation with non-contrast CT CAC score. This could imply a radiation dose reduction and time saving by omitting the non-contrast scan.

Coronary computed tomography angiography (CTA) has important prognostic value. Additionally, quantitative CTA (QCT) provides a more detailed accurate assessment of coronary artery disease (CAD) on CTA. Potentially, a risk score incorporating all quantitative stenosis parameters allows accurate risk stratification. Therefore, the purpose of this study was to determine if an automatic quantitative assessment of CAD using QCT combined into a CTA risk score allows risk stratification of patients. In 300 patients, QCT was performed to automatically detect and quantify all lesions in the coronary tree. Using QCT, a novel CTA risk score was calculated based on plaque extent, severity, composition, and location on a segment basis. During follow-up, the composite end point of all-cause mortality, revascularization, and nonfatal infarction was recorded. In total, 10% of patients experienced an event during a median follow-up of 2.14 years. The CTA risk score was significantly higher in patients with an event (12.5 [interquartile range 8.6 to 16.4] vs 1.7 [interquartile range 0 to 8.4], p <0.001). In 127 patients with obstructive CAD (≥50% stenosis), 27 events were recorded, all in patients with a high CTA risk score. In conclusion, the present study demonstrated that a fully automatic QCT analysis of CAD is feasible and can be applied for risk stratification of patients with suspected CAD. Furthermore, a novel CTA risk score incorporating location, severity, and composition of coronary lesion was developed. This score may improve risk stratification but needs to be confirmed in larger studies., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Background: Coronary lesions with a diameter narrowing ≥50% on visual computed tomographic coronary angiography (CTCA) are generally considered for referral to invasive coronary angiography. However, similar to invasive coronary angiography, visual CTCA is often inaccurate in detecting functionally significant coronary lesions. We sought to compare the diagnostic performance of quantitative CTCA with visual CTCA for the detection of functionally significant coronary lesions using fractional flow reserve (FFR) as the reference standard., Methods and Results: CTCA and FFR measurements were obtained in 99 symptomatic patients. In total, 144 coronary lesions detected on CTCA were visually graded for stenosis severity. Quantitative CTCA measurements included lesion length, minimal area diameter, % area stenosis, minimal lumen diameter, % diameter stenosis, and plaque burden [(vessel area-lumen area)/vessel area×100]. Optimal cutoff values of CTCA-derived parameters were determined, and their diagnostic accuracy for the detection of flow-limiting coronary lesions (FFR≤0.80) was compared with visual CTCA. FFR was ≤0.80 in 54 of 144 (38%) coronary lesions. Optimal cutoff values to predict flow-limiting coronary lesion were 10 mm for lesion length, 1.8 mm2 for minimal area diameter, 73% for % area stenosis, 1.5 mm for minimal lumen diameter, 48% for % diameter stenosis, and 76% for plaque burden. No significant difference in sensitivity was found between visual CTCA and quantitative CTCA parameters (P>0.05). The specificity of visual CTCA (42%; 95% confidence interval [CI], 31%-54%) was lower than that of minimal area diameter (68%; 95% CI, 57%-77%; P=0.001), % area stenosis (76%; 95% CI, 65%-84%; P<0.001), minimal lumen diameter (67%; 95% CI, 55%-76%; P=0.001), % diameter stenosis (72%; 95% CI, 62%-80%; P<0.001), and plaque burden (63%; 95% CI, 52%-73%; P=0.004). The specificity of lesion length was comparable with that of visual CTCA., Conclusions: Quantitative CTCA improves the prediction of functionally significant coronary lesions compared with visual CTCA assessment but remains insufficient. Functional assessment is still required in lesions of moderate stenosis to accurately detect impaired FFR.

Though conventional coronary angiography (CCA) has been the standard of reference for diagnosing coronary artery disease in the past decades, computed tomography angiography (CTA) has rapidly emerged, and is nowadays widely used in clinical practice. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms devised to detect and quantify the coronary artery stenoses, and to segment the coronary artery lumen in CTA data. The objective of this evaluation framework is to demonstrate the feasibility of dedicated algorithms to: (1) (semi-)automatically detect and quantify stenosis on CTA, in comparison with quantitative coronary angiography (QCA) and CTA consensus reading, and (2) (semi-)automatically segment the coronary lumen on CTA, in comparison with expert's manual annotation. A database consisting of 48 multicenter multivendor cardiac CTA datasets with corresponding reference standards are described and made available. The algorithms from 11 research groups were quantitatively evaluated and compared. The results show that (1) some of the current stenosis detection/quantification algorithms may be used for triage or as a second-reader in clinical practice, and that (2) automatic lumen segmentation is possible with a precision similar to that obtained by experts. The framework is open for new submissions through the website, at http://coronary.bigr.nl/stenoses/., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Purpose: Automated software tools have permitted more comprehensive, robust and reproducible quantification of coronary stenosis, plaque burden and plaque location of coronary computed tomography angiography (CTA) data. The association between these quantitative CTA (QCT) parameters and the presence of myocardial ischaemia has not been explored. The aim of the present investigation was to evaluate the association between QCT parameters of coronary artery lesions and the presence of myocardial ischaemia on gated myocardial perfusion single-photon emission CT (SPECT)., Methods: Included in the study were 40 patients (mean age 58.2 ± 10.9 years, 27 men) with known or suspected coronary artery disease (CAD) who had undergone multidetector row CTA and gated myocardial perfusion SPECT within 6 months. From the CTA datasets, vessel-based and lesion-based visual analyses were performed. Consecutively, lesion-based QCT was performed to assess plaque length, plaque burden, percentage lumen area stenosis and remodelling index. Subsequently, the presence of myocardial ischaemia was assessed using the summed difference score (SDS ≥2) on gated myocardial perfusion SPECT., Results: Myocardial ischaemia was seen in 25 patients (62.5%) in 37 vascular territories. Quantitatively assessed significant stenosis and quantitatively assessed lesion length were independently associated with myocardial ischaemia (OR 7.72, 95% CI 2.41-24.7, p < 0.001, and OR 1.07, 95% CI 1.00-1.45, p = 0.032, respectively) after correcting for clinical variables and visually assessed significant stenosis. The addition of quantitatively assessed significant stenosis (χ(2) = 20.7) and lesion length (χ(2) = 26.0) to the clinical variables and the visual assessment (χ(2) = 5.9) had incremental value in the association with myocardial ischaemia., Conclusion: Coronary lesion length and quantitatively assessed significant stenosis were independently associated with myocardial ischaemia. Both quantitative parameters have incremental value over baseline variables and visually assessed significant stenosis. Potentially, QCT can refine assessment of CAD, which may be of potential use for identification of patients with myocardial ischaemia.

Plaque constitution on computed tomography coronary angiography (CTA) is associated with prognosis. At present only visual assessment of plaque constitution is possible. An accurate automatic, quantitative approach for CTA plaque constitution assessment would improve reproducibility and allows higher accuracy. The present study assessed the feasibility of a fully automatic and quantitative analysis of atherosclerosis on CTA. Clinically derived CTA and intravascular ultrasound virtual histology (IVUS VH) datasets were used to investigate the correlation between quantitatively automatically derived CTA parameters and IVUS VH. A total of 57 patients underwent CTA prior to IVUS VH. First, quantitative CTA quantitative computed tomography (QCT) was performed. Per lesion stenosis parameters and plaque volumes were assessed. Using predefined HU thresholds, CTA plaque volume was differentiated in 4 different plaque types necrotic core (NC), dense calcium (DC), fibrotic (FI) and fibro-fatty tissue (FF). At the identical level of the coronary, the same parameters were derived from IVUS VH. Bland-Altman analyses were performed to assess the agreement between QCT and IVUS VH. Assessment of plaque volume using QCT in 108 lesions showed excellent correlation with IVUS VH (r = 0.928, p < 0.001) (Fig. 1). The correlation of both FF and FI volume on IVUS VH and QCT was good (r = 0.714, p < 0.001 and r = 0.695, p < 0.001 respectively) with corresponding bias and 95 % limits of agreement of 24 mm(3) (-42; 90) and 7.7 mm(3) (-54; 70). Furthermore, NC and DC were well-correlated in both modalities (r = 0.523, p < 0.001) and (r = 0.736, p < 0.001). Automatic, quantitative CTA tissue characterization is feasible using a dedicated software tool. Fig. 1 Schematic illustration of the characterization of coronary plaque on CTA: cross-correlation with IVUS VH. First, the 3-dimensional centerline was generated from the CTA data set using an automatic tree extraction algorithm (Panel I). Using a unique registration a complete pullback series of IVUS images was mapped on the CTA volume using true anatomical markers (Panel II). Fully automatic lumen and vessel wall contour detection was performed for both imaging modalities (Panel III). Finally, fusion-based quantification of atherosclerotic lesions was based on the lumen and vessel wall contours as well as the corresponding reference lines (estimate of normal tapering of the coronary artery), as shown in panel IV. At the level of the minimal lumen area (MLA) (yellow lines), stenosis parameters, could be calculated for both imaging techniques. Additionally, plaque volumes and plaque types were derived for the whole coronary artery lesion, ranging from the proximal to distal lesion marker (blue markers). Fibrotic tissue was labeled in dark green, Fibro-fatty tissue in light green, dense calcium in white and necrotic core was labeled in red.

Aims: Previous studies have used semi-automated approaches for coronary plaque quantification on multi-detector row computed tomography (CT), while an automated quantitative approach using a dedicated registration algorithm is currently lacking. Accordingly, the study aimed to demonstrate the feasibility and accuracy of automated coronary plaque quantification on cardiac CT using dedicated software with a novel 3D coregistration algorithm of CT and intravascular ultrasound (IVUS) data sets., Methods and Results: Patients who had undergone CT and IVUS were enrolled. Automated lumen and vessel wall contour detection was performed for both imaging modalities. Dedicated automated quantitative software (QCT) with a unique registration algorithm was used to fuse a complete IVUS run with a CT angiography volume using true anatomical markers. At the level of the minimal lumen area (MLA), percentage lumen area stenosis, plaque burden, and degree of remodelling were obtained on CT. Additionally, mean plaque burden was assessed for the whole coronary plaque. At the identical level within the coronary artery, the same variables were derived from IVUS. Fifty-one patients (40 men, 58 ± 11 years, 103 coronary arteries) with 146 lesions were evaluated. Quantitative computed tomography and IVUS showed good correlation for MLA (n = 146, r = 0.75, P < 0.001). At the level of the MLA, both techniques were well-correlated for lumen area stenosis (n = 146, r = 0.79, P < 0.001) and plaque burden (n = 146, r = 0.70, P < 0.001). Mean plaque burden (n = 146, r = 0.64, P < 0.001) and remodelling index (n = 146, r = 0.56, P < 0.001) showed significant correlations between QCT and IVUS., Conclusion: Automated quantification of coronary plaque on CT is feasible using dedicated quantitative software with a novel 3D registration algorithm.

Objectives: This study sought to demonstrate the feasibility of a dedicated algorithm for automated quantification of stenosis severity on multislice computed tomography in comparison with quantitative coronary angiography (QCA)., Background: Limited information is available on quantification of coronary stenosis, and previous attempts using semiautomated approaches have been suboptimal., Methods: In patients who had undergone 64-slice computed tomography and invasive coronary angiography, the most severe lesion on QCA was quantified per coronary artery using quantitative coronary computed tomography (QCCTA) software. Additionally, visual grading of stenosis severity using a binary approach (50% stenosis as a cutoff) was performed. Diameter stenosis (percentage) was obtained from detected lumen contours at the minimal lumen area, and corresponding reference diameter values were obtained from an automatic trend analysis of the vessel areas within the artery., Results: One hundred patients (53 men; 59.8 +/- 8.0 years) were evaluated, and 282 (94%) vessels were analyzed. Good correlations for diameter stenosis were observed for vessel-based (n = 282; r = 0.83; p < 0.01) and patient-based (n = 93; r = 0.86; p < 0.01) analyses. Mean differences between QCCTA and QCA were -3.0% +/- 12.3% and -6.2% +/- 12.4%. Furthermore, good agreement was observed between QCCTA and QCA for semiquantitative assessment of diameter stenosis (accuracy of 95%). Diagnostic accuracy for assessment of > or =50% diameter stenosis was higher using QCCTA compared with visual analysis (95% vs. 87%; p = 0.08). Moreover, a significantly higher positive predictive value was observed with QCCTA when compared with visual analysis (100% vs. 78%; p < 0.05). Although the visual approach showed a reduced diagnostic accuracy for data sets with moderate image quality, QCCTA performed equally well in patients with moderate or good image quality. However, in data sets with good image quality, QCCTA tended to have a reduced sensitivity compared with visual analysis., Conclusions: Good correlations were found for quantification of stenosis severity between QCCTA and QCA. QCCTA showed an improved positive predictive value when compared with visual analysis., (Copyright 2010 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Efficiently obtaining a reliable coronary artery centerline from computed tomography angiography data is relevant in clinical practice. Whereas numerous methods have been presented for this purpose, up to now no standardized evaluation methodology has been published to reliably evaluate and compare the performance of the existing or newly developed coronary artery centerline extraction algorithms. This paper describes a standardized evaluation methodology and reference database for the quantitative evaluation of coronary artery centerline extraction algorithms. The contribution of this work is fourfold: (1) a method is described to create a consensus centerline with multiple observers, (2) well-defined measures are presented for the evaluation of coronary artery centerline extraction algorithms, (3) a database containing 32 cardiac CTA datasets with corresponding reference standard is described and made available, and (4) 13 coronary artery centerline extraction algorithms, implemented by different research groups, are quantitatively evaluated and compared. The presented evaluation framework is made available to the medical imaging community for benchmarking existing or newly developed coronary centerline extraction algorithms.